Archive for the 'google earth' Category

Nov 01 2011

Google Maps new MapsGL engine – heavy use and lots of love

Published by under Google Maps MapsGL

I’ve got a version of streams set up, and we’re poised to update our terrain before running through some cycles of review and revision.

But first, I need to get our community base map updated, and that’s been one detour after another it seems.  An innocent-sounding reviewer request to straighten out our parks has led to a months-long campaign of updating shoreline, lower-low water inundation, the judicious trimming of private parcels at the high water line, the representation of park lands both named and parceled as well as public access spaces in the intertidal reaches, and more.  That more has involved a serious effort to accurately represent our marsh lands in terms of tidal channels, mud flats, and vascular marsh vegetation—all of it based on aerial photography and much of it derived from our latest National Agricultural Imagery Program (NAIP) 1-meter 4-band imagery, which has proven very high quality both in spatial edge content as well as dynamic range of lighting.  Marsh features both current and fading in less-than-vigorously reclaimed land have been given much attention.  The details are covering the Petaluma River marsh (downstream of the outflow of San Antonio Creek waters into the Petaluma River) and the Petaluma River banks.

But that led to the latest  detour: those massive steel lattice towers that support electrical transmission lines.  They’re actually very significant landmarks, as well as eminently mappable features.  They were easy, but led to harder stuff: the sub-transmission network.  It’s like you start out with the easy 240 kV lines, and then come back for more.  One day it’s just a few big towers, and then the next thing you know, one’s back for 120 kV, and maybe 64 kV and 32 kV rural lines too.  You know it’s bad when you can’t stop and you just want to locate a few more poles to make it to the next county line…  And then one day you wake up and it’s been 10,000 poles.  ;^)

Anyhow, as a result of what began as a mappable affront to wetland areas, tidal marshes in particular, has now turned into a draft electrical transmission and sub-transmission (not single-house distribution) network feature class.  Turns out that the NAIP 2010 imagery, together with 10cm imagery from 2004 in the urban areas and various 30cm sources in other areas and years has been quite enough to dial in  public utility assets, frequently constructed in public rights-of-way, extracted using basic geospatial intellgence techniques applied to publicly available imagery resources.  The catalyst has been the evolved Google Maps MapsGL viewer engine.

I’ve only started to use MapsGL intensively in the past 10 days or so, but it is astoundingly well integrated.  Right now, I have the sense that there is nothing else quite like it out there for public use.  The interface experience was very different at once, and the viewer actually suggested that I try it when I was very actively moving between 2D map view and Street View, using the mouse wheel.  When I switched over to the new viewer, I was very pleasantly shocked.  The 2D “satellite” view, the “45-degree” views, and Street View were all smoothly mediated by a 3D model textured with imagery from the 45-degree views—using features from the Google Earth plugin.

It was shocking, and something that got me to jump out of my chair to share with a colleague, when I realized that the Earth view was being used to generate a transition between different rotations of the 45-degree view.  Sound obscure?  Consider an oblique 45-degree view looking default north, where you want to look toward the west instead.  Click the compass ring and it will turn, as expected.  What’s not expected (at first) is that the oblique view transition, rather than blanking out and plopping the next view onto the screen, instead puffs out to become a textured 3D sculpty model.  Yes, that means that the buildings, terrain, and trees are shown as they might be when very far zoomed in on Google Earth, and then that view rotates just like it would in a well-handled Second Life viewer, until it settles into the new oblique direction, after which the 3D effect fades and the oblique is presented.

But in one’s mind, crucially, the 3D impression remains and informs the interpretability of the the oblique.  The tree that covers the back part of the house now has been ascribed a 3D volume in the user/analyst’s mind, and suddenly makes more sense than the flat 45-degree view would on its own.

Even without the obliques as an intermediary, popping from 2D map view to Street View is mediated by the virtual reality of textured 3D sculpty objects, and this helps make the Street View perspective far more readable in an instant after arrival.

From my perspective, the MapsGL interface engine is a major evolution of 3D GIS–because it uses a simulated 3D textured surface space to mediate among 2D vertical orthoimagery, 2D oblique imagery, and panoramic ground-level imagery.  That it’s public and cost-free makes it compelling to use for meaningful applications.  In the past few days, I’ve been able to follow sub-transmission pole sequences through fairly rugged forested suburban settings, because my GIS-based moderately detailed imagery allows me to digitize whatever I can see or estimate, while on a full adjacent screen, MapsGL provides sharper orthoimagery, frequent oblique views in urban and adjacent areas, and Street View to tenaciously follow lines as they pass under tree canopy along roadways.

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Mar 30 2011

Holy Cow! Earth arrives in Google Maps – with obliques

Months ago I’d noticed some cool oblique aerials showing up in Google Maps in the vicinity of Mountain View.  So nice to imagine a world with Pictometry-type imagery that was not just in Bing Maps.

 

Well, today I saw that Marin county, and at least Berkeley, CA and Gettysburg, PA now have oblique imagery in Google Maps, somewhere between the vertical aerial scales and the StreetView Scales.  It’s great to see, but that’s not all I noticed.

As I poked around, I hovered near the Maps button and Traffic view, and out pops an Earth button.  Have I seen this before?  I tried it out and whoosh!  I got the Google Earth plugin going with no effort.  Almost made me glad to be using Windows ;^)

 

Google Earth view of Berkeley, with 3D Warehouse buildings—as part of Google Maps (in Windows)

 

The interface tweaks to Earth in Maps are brilliant IMHO.  There is a hyperbolic path that brings people in from a vertical view to something reasonably horizontal.  All the keyboard navigation controls are there, and the two buttons to modify look direction and look location are exquisite.  Props to the Earth plugin team!

It’s pheonomenal to have both excellent-quality obliques and seamless Earth integration show up all at once.  I hope that the folks at Cal GIS 2011 in Fresno find out about this in time to collectively digest it all.  Here at Marin, we’re recognizing a big jump in the importance of having decent building masses uploaded for public consumption.

Update:  Yes, I have realized that Google Maps Earth View was announced way back in 2010.04, nearly a year ago.  I guess that it’s a measure of how much time I’ve spent in Unbutu Linux or on Android that I haven’t realized it — because Earth View still hasn’t arrived in those platforms!

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Mar 14 2011

Shaken Awake – and new terrain product

The enormously tragic megathrust event east of Honshu island in Japan has been in my thoughts throughout the weekend.   It is natural to focus on the human loss and images of civic destruction; I’ve got little to add to that story.

When I saw the first news items, it was already Friday morning and eight hours past the event.  My concerns were for Hawaii and the arrival of a tsunami.  I was shocked by the energy released, as reported at NEIC:  Mo=3.9×10^22 Nm,  Mw=9.0 — for as many earthquakes as have been recorded and studied in Japan, this was a much larger event.  For disaster planning, that is Not A Good Thing.

Moment Tensor USGS/WPHASE  Mo=3.9x10^22 Nm

The beach ball diagram shows compression back up the thrust. Depth of event is 24km

While there was some concern for Hawaii, there is something to be said for the diffraction caused by the long line of seamounts extending northwesterly from the big island.  While the energy won’t be cancelled out, the height of the crest would be widened some.  By the time the tsunami reached California, it was a real concern and a literal wake-up call for emergency workers.  Our damage here was mostly an economic annoyance, with Del Norte county once again taking the brunt of the damage in Crescent City harbor.

With a check-in call to relatives in Hawaii saying everything OK, their eyes and mine turned towards Japan.  As I watched shocking videos of tsunami damage, I struggled to calibrate what I was seeing with my mental model of how fragile most human habitation structures are.  I’ve thought much about the effects of shaking, liquefaction, and occasionally about wildland fire.  I’ve read about losses in Marin county during 1982 flooding where debris flows destroyed houses or literally rolled them end-over-end down a slope.  I’d seen some videos from near Sumatra of debris flowing up streets after waves climbed up the beach.  Yet images from Japan recorded damage unfolding at an entirely worse scale.

My concern became much more engaged when I saw helicopter video of the south end of nuclear power reactor facility Fukushima Daiichi (No. 1).  You see, in the video clip I recognized not the reactor, but the cut slope behind it.  In a very strange sense of model-based deja vu, my memories were unequivocal: “I know that place!”.

Why?  Because about 17 or 18 years ago, I was fortunate to be part of a site design project for the (still yet to be constructed) Unit 7 and Unit 8 reactors.  Fortunate for me, because it was a first opportunity to learn not just ESRI Arc/INFO, but how to work with Bentley CAD software to create a 3D cut slope design.  My small contribution was to create a realization of slope that was  not simply faceted as a buffer surrounding the building footprints, but instead create a semblance of the natural cliff slopes  adjacent to the plant, while meeting the engineering requirements for not-to-exceed slope steepness, and a more natural-looking accumulation of drainage from the slope.

So apparently, after spending a couple of weeks learning to use 3D design software and creating a design that extended the existing cut farther southward, I had an image of the plant, its cliffs, and the breakwater that guided cooling water that stuck with me.  After having the flash of recognition with the video, I opened up Google Maps and found the site on my first inward zoom.  It was a bit spooky.

So now when I watch coverage of hydrogen venting that leads to building explosions, I feel a curious terrain-based sense of connection with the site.  I wish them well, and the safest possible return to production.  The TEPCO power is needed by many people.

And more ominous for the Pacific Northwest, I can’t help but reflect on what a similar megathrust event would mean for Cascadia.  Both Portland and Seattle would be in some sort of peril, although I don’t have a clear understanding of how tsunamis are modeled for either lower Columbia River or for Puget Sound.  But the possibility of a 9.0 megathrust event along the Cascadia subduction zone was a whole lot more abstract for me until last Friday.  It may not be the best time to reflect on it now while Japan is suffering—but the risk to the northwest has been a matter of public record for several years now and it not the time to forget that, either.  An event of that size and location would have tsunami implications both locally, and perhaps a far greater risk for windward Hawaii.

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Closer to home,  this past week we’ve created a prototype 3D product that provides a facsimile of our 45cm terrain model—imported to Google SketchUp 8 with a georeferenced orthophoto texture on the terrain.  Things are not fully tuned up yet, but we are able to take TIN and decimated TIN surfaces out of ArcGIS 10, by way of clipping polygons that are interpolated to multipatch (3D multi-polygon features) and then exported to Collada with a KML point for georeference.  The Collada can be imported to SketchUp, at least up so some limit of detail.  Once there, I’m trying now to find the right way to smooth the facets and improve the rendering of the surface without having high-contrast dark facets—because the orthophoto textures are arriving intact and draping over the surface.  Only at the moment, many black facets are covering up almost half of the orthophoto in an aggravating triangular patchwork.

Next step: smoothing within SketchUp.

And inspiration from others who have gotten gridded terrain into SketchUp.

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Sep 26 2010

Meandering into mobile map delivery

Published by under GIS in general,google earth

Opensim has slipped to a back burner for these past few weeks, as I button up a new edition of county terrain–this one fused topography and bathymetry.
Another focus has been to compile the map data layers necessary to publish a local edition of the large-scale topographic map, using the ESRI Community Maps Program template. This (Opensim-distracting) work forms a synergy, as the terrain drives revised hillshade and topo-bathy contour lines, as well as forming the basis for refined surface flow and stream mapping, all of which show up in the large-scale topo map. Also, I’ve compiled a great deal of web research into a single feature layer: classified building footprints, many of which have use categories [commercial, medical, educational, religious, etc.] and specific organization names included, for every structure on the associated parcel.

Why generate this large-scale topographic base map? It’s purpose is to provide local control over local detail, in a cloud-based service suitable for desktop, tablet, and mobile phone users who may consume applications that mash or overlay the base map with relatively sparse point or line features. While we’ll be able to serve up the base map through our own MarinMap servers, one of the key benefits of the conforming large-scale topographic map style (as made possible by the template) is that the caches of the four largest-scale views will be rendered and contributed for inclusion in the ArcGIS Online map services, as viewed at arcgis.com and consumable by many interactive map sites. The cached map tiles are essentially raster prints of the map template (which has styles customized at four local zoom levels) that can be served extremely fast.

Those fast maps can also be efficient, for mobile phones and tablets consuming base maps with no special rendering. Along that path, I’ve rebuilt my mobile phone this past week, taking the T-Mobile G1 and rooting it, then installing various new images until I found one that was up-to-date, stable, and attractive to use. As of this weekend, I’m now running Chromatic 4.5 with SetCPU 3.0.2 overclocking. Chromatic 4.5 is a packaging of CyanogenMod 6.0.0 with the ADW launcher and many other tunes. CyanogenMod 6.0.0 is an Android Open Source Project-based build of Android version 2.2 “Froyo”. So now, when I view maps and browser content, I can pinch to zoom out, spread to zoom in, and still push around the map to pan it on the screen. As part of sharing content with mobile phones, I’ve learned how to generate QR tags to provide access to map URL or geolocation tags.

For fun today, we visited the Silicon Valley area to show a guest some of the sights. I hadn’t visited the Googleplex in a couple of years, and many of the adjacent buildings that I recall as having different companies in them are now part of the Google campus. We found one interesting sight, too–and it appears that today may have been Google Inc.’s 12th birthday. We didn’t see any partying in the mostly-empty parking lots, which wasn’t surprising for a Sunday!

At the Googleplex 2010 09 26

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Mar 12 2010

Sharing Terrain With the World – Google Earth style

It’s not fully 3D immersive, but hey, 2-1/2D ain’t half bad. The “dsm40cm” model of Marin County has been published as the county’s default terrain on Google Earth. It’s a great pleasure to work with folks who are not troubled by a county representing its surface on a 40cm single-precision float grid that weighs in at 77 GB. In terms of data bulk, that is about the same as the entire 30-meter version of the US National Elevation Dataset.

What one gets when piling that much detail into a single county of around 520 square miles of land area is every building pad, driveway, and crown of road paving that were resolved. The dsm40cm model was derived from an ESRI Terrain Dataset that incorporates our best available topographic contours (1:4800 scale 10-foot; 1:2400 scale 2-foot,) photogrammetric break and water lines, FEMA LiDAR and NCALM (GeoEarthScope) LiDAR data sets. The Terrain Dataset currently comprises 40 GB of vector GIS data.

When the finely detailed surface grids were first developed, we broke the county up into 20 work areas to maintain ArcGIS 9.3.1 in a stable and productive state, and 30cm posting interval grids were generated that covered the entire county–at least during development. When necessary, these grid tiles were mosaicked with ERDAS Imagine into a single seamless grid. The 40cm version was produced directly as a single seamless grid using ArcGIS 9.4 beta 1, on a workstation imaged with Windows Server 2003. The WGS84 UTM, NAVD88-Geoid 2003 result was provided to the Google Earth team earlier this year.

As with all GIS data sets, it seems, the more detailed it is, the more rapidly it may need updating. In the works for the next year or so are several improvements to the dsm40cm model. First: the photogrammetric break lines will be segregated into steeper sets that tend to run along ridges, and shallower slopes that tend to delineate road cuts and building pads. The ridge set will be used as soft constraints to resolve some artifacts where they rise above some contours.
Second: incorporate new LiDAR data as it becomes available. Some data has already been provided for the lowest part of Lagunitas creek, and it appears that Prof. Ellen Hines of San Francisco State University’s Department of Geography and Human Environmental Studies has been funded by USGS to gather LiDAR county-wide this year.

So there will be revisions, but an exciting aspect is to see data flows being brought into existence that support different levels of mirror world development.
Publishing the dsm40cm model in Google Earth is an important (and beautiful) threshold to cross. Making use of the dsm40cm model in county operations such as creek and watershed delineation will be the practical benefit that drives the work in the first place. And before too many more weeks, there may be entirely new approaches to publishing the data in an immersive environment (neither Second Life nor Opensim) to share.

Building pad in Kent Woodlands shows driveway-level detail

Kent Woodlands building pad and driveway, in the shadow of Mt. Tam

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May 24 2009

Some thoughts on geography

updated 2009 05 26

I’ve been waiting for some property boundary issues to resolve in SL, and it’s sort of pitiful to see how long that can take.  It’s with ever more regret that I find myself on the Mainland.  But that hasn’t kept lots of real-world interesting stuff from taking shape.

The following video is not new.  In fact it’s about a year old, but somehow I hadn’t seen it until tonight and I found it somewhat encouraging. Thanks for O’Reilly and Where 2.0 for bringing these two on stage together!

And the following pean to Google Earth did inspire me, personally. Hey, I was reading road maps at 5, covered my wall completely with National Geographic maps at 10, learned to navigate with nautical charts at 12, read aeronautical charts and completed an urban planning project at 14. Sometimes, it’s fun in rare moments when it’s dark overcast and I’m in an exotic place for the first time and I don’t know the way north; more often, I’ll savor the feeling of knowing which way is north while dreaming.

Meanwhile, back at the lab, the global set of county terrain is being compiled into an ESRI Terrain Dataset. This will include over 360 million masspoints, merging both interpolated 2-foot interval contour vertices together with FEMA LiDAR mass points, plus break lines and waterlines from photogrammetry. The goal is to use the ESRI Terrain data as a format to stage everything together to produce 30cm grid interval DEM in the urban areas. With luck, we’ll have that ready about the time that the latest photo mosaic finally gets loaded into ArcSDE successfully. Maybe grids from the Terrain can help create very detailed 3D county models. Hey Wei – we still have inverted terrain in Google Earth at the quarry on San Pedro Point! ;^)

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Apr 22 2009

Something new for Earth Day

<<updated 20090424>>

As my patience with Second Life wanes, and I wait for more architectural input for my next SL build project, I have a dark OpenSim server with no fixed IP.  I’m having stability issues with the Linux SL client, but have upgraded the workstation to Ubuntu 9.04 Jaunty Jackalope.  Google Earth client there is more stable, the NVidia drivers install themselves (sans Envy), and everything Ubuntu-wise seems to be getting incrementally better by the quarter.

I’m grinding some large images that have taught me that one very special difference between Windows XP variants and Windows Server 2003 is the latter’s ability to open files on the high side of 80 GB.  I’d never quite realized it before but the moderately massive mosaics that I have created in years past (edging toward 250 GB single files) actually depended on Server 2003 to get created.  Once the destination file exists, then XP can take it from there, and in all cases Windows Explorer can copy the monster files.  But in that tenuous moment when a mosaic first grabs its space on disk for a huge output—one can’t seem to do that with XP.

So while I’m enjoying Google Earth on Ubuntu, there is something cool that I go back to Windows for, and that’s the new Google Earth browser plug-in.  Since I’m gaining a bit of facility with the keyboard shortcuts in the full-stop Earth client, these all carry over to the plugin.  My first test page has been stood up here and I’ve been deep into four continents with it so far.  I understand that the plugin is only available for Windows and Mac systems at this time.  If you can,  Enjoy!

http://earth.jedi.bz 

Also, as I get even faster with my keyboard navigation of G-Earth, I’ve actually seen some artifacts that are quite familiar from OpenSim.  While zipping about between the Gulf of Yakutat and Canada’s Mount Logan, at certain viewing elevations I can accelerate the point of view forward quite fast.  Doing so in this very mountainous terrain, I saw blocks of terrain standing up along what look like sim edges, resolving in a few seconds as more (sculpty?) bumpmap arrives.  This is the same sort of artifact I’ve seen with terrain sculpties and sometimes, with region crossings in OpenSim.  Also, I’ve found a couple of wild terrain grid errors in G-Earth.  In one, a quarry dug hundreds of feet below sea level, right next to the sea, is displayed as positive elevation (absolute-value terrain, anyone?).  In another, a boundary between US and Canadian terrain has a glacier flowing uphill onto a plateau.  Go figure.  Blame Canada! ;^)

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